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engineering methodology中文是什么意思

  • 工程方法論

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  • 例句與用法
  • The application of the software covers more and more widely with the improvement of the theory of software engineering methodologies and the ripeness of the software developer
    隨著軟件工程方法學理論的進步、軟件開發(fā)人員的成熟,計算機軟件的應用覆蓋面越來越大。
  • Modern software development adopts engineering methodology to manage developing of software , it emphasizes on the software quality control and try to reduce the risk in software development by taking appropriate measures
    現(xiàn)代軟件開發(fā)采用工程化的方法對開發(fā)活動進行管理,重視對質量的控制,采取相關的措施降低開發(fā)風險。
  • Service engineering methodology was discussed and reviewed from its five components of the framework , namely service meta - model , service modeling approach , service system development approach , service performance evaluation , and relevant supporting tools
    依據(jù)該框架的服務元模型、服務建模、服務系統(tǒng)構建、服務性能評價和相關支持工具五個要素,綜述了服務工程方法。
  • The most advance software - engineering methodology was presented , for example the oop , com , compiler technology and so on . , which are used to design and develop the component modeling and simulation application framework of the tgcs
    本論文仿真軟件的實現(xiàn)采用了最先進的軟件工程方法? ?面向對象技術、組件技術、編譯技術,由此設計和開發(fā)了的魚雷制導系統(tǒng)仿真環(huán)境。
  • Now , the development of management information system ( mis ) is guided by information engineering methodology whose base idea is that data is the center of information processing and data is steady but processing is changeable . the method is important to program , analyze and design mis
    目前,管理信息系統(tǒng)( mis )的開發(fā)大部分采用信息工程方法論為指導,它的基本思想和原則是:數(shù)據(jù)位于現(xiàn)代信息處理中心,數(shù)據(jù)是穩(wěn)定的,而處理是多變的。
  • According to the requirements of operation of blast furnace and software engineering methodology , the properties and function of prototype of prediction system have been analyzed and hierarchical structure and data flow and data processing in the system have been outlined by using data flow diagram
    根據(jù)高爐生產的需求以及軟件工程理論,系統(tǒng)分析了預測軟件的性能要求與模塊組成,以系統(tǒng)數(shù)據(jù)流程圖逐層分析了信息流在軟件系統(tǒng)中的流動、變換和處理情況。
  • Uml is the convergence of best practices in the object - technology industry . and it is a rich ; precise , extensible modeling language for object - oriented system development and software developing automation environments . uml is the representation of excellent software engineering methodology which is approbatory in large - scale and complex modeling field
    它涵蓋了面向對象的分析、設計和實現(xiàn),融合了早期面向對象建模方法和各種建模語言的優(yōu)點;為面向對象系統(tǒng)的開發(fā)、軟件自動化工具與環(huán)境提供了豐富的、嚴謹?shù)?、擴充性強的表達方式。
  • Also , the existing problems are formulized to illustrate the applying situation of iec61499 standard in our country . secondly , a complex application system is constructed based on the iec61499 standard and model - view - control ( mvc ) design pattern , and then , a related engineering methodology is introduced
    在iec61499標準和模型-視圖-控制器( mvc )設計模式的基礎上,構造了一個較為復雜的控制應用系統(tǒng),并由此摸索出一套基于mvc設計模式的功能塊系統(tǒng)設計方法。
  • In this thesis , a new model used for prediction of silicon content in hot metal based on self - organized experience evolution approach has been investigated by developing prototype of the model with software engineering methodology , optimizing model parameters and testing it with process data of blast furnace in tianjin iron plant
    針對目前鐵水硅含量預測方法尚不能滿足高爐過程控制需要的現(xiàn)狀,根據(jù)所提出的高爐鐵水硅含量自組織經驗進化預測模型原理,用軟件工程方法學設計和開發(fā)了相應軟件原型,并從理論和實踐角度對這種新的智能預測模型進行了研究。
  • However , existing models till now which used for the prediction and controlling of silicon content in hot metal could n ' t meet the requirement to control such a complex processing of blast furnace . in this thesis , a new model used for predicting and controlling silicon content in hot metal based on artificial neural networks ( anns ) and expert system has been investigated by developing prototype of the model with software engineering methodology , after inquiring about the parameters which could affect silicon content in hot metal with the operators of blast furnace
    本研究即是針對目前硅含量的預報和控制方法不能滿足實際高爐生產過程控制需要,在對高爐鐵水硅含量影響因素及控制知識進行收集、分析的基礎上,結合鐵水硅含量控制過程中的諸多不確定因素,提出了將神經網絡、專家系統(tǒng)共同作用于高爐鐵水硅含量的預報、控制模型。
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